Multidimensional Descriptor Indexing: Exploring the BitMatrix

Calistru, Catalin; Ribeiro, Cristina; David, Gabriel

doi:10.1007/11788034_41

Cited by 9 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[10] introduces the Vector Approximation (VA) File approach, a method based on signatures for improving efficiency in processing feature vectors. Similar approaches can be found, e.g., in iGrid [11] and BitMatrix [12]. …”

Section: Related Workmentioning

confidence: 90%

ADAM - A Database and Information Retrieval System for Big Multimedia Collections

Giangreco

Kabary

Schuldt

2014

2014 IEEE International Congress on Big Data

View full text Add to dashboard Cite

The past decade has seen the rapid proliferation of low-priced devices for recording image, audio and video data in nearly unlimited quantity. Multimedia is Big Data, not only in terms of their volume, but also with respect to their heterogeneous nature. This also includes the variety of the queries to be executed. Current approaches for searching in big multimedia collections mainly rely on keywords. However, manually annotating every single object in a large collection is not feasible. Therefore, content-based multimedia retrieval -using sample objects as query input-is increasingly becoming an important requirement for dealing with the data deluge. In image databases, for instance, effective methods exploit the use of exemplary images or hand-drawn sketches as query input. In this paper, we introduce ADAM, a novel multimedia retrieval system that is tailored to large collections and that is able to support both Boolean retrieval for structured data and similarity-based retrieval for feature vectors extracted from the multimedia objects. For efficient query processing in such big multimedia data, ADAM allows the distribution of the indexed collection to multiple shards and performs queries in a MapReduce style. Furthermore, it supports a signature-based indexing strategy for similarity search that heavily reduces the query time. The efficiency of ADAM has been successfully evaluated in a content-based image retrieval application on the basis of 14 million images from the ImageNet collection.

show abstract

Section: Related Workmentioning

confidence: 90%

ADAM - A Database and Information Retrieval System for Big Multimedia Collections

Giangreco

Kabary

Schuldt

2014

2014 IEEE International Congress on Big Data

View full text Add to dashboard Cite

show abstract

“…To illustrate the use of the framework on a new indexing method, we will now use the BitMatrix [9], a method we have been developing for multimedia database applications. The BitMatrix method follows a data approximation approach in the spirit of VA-File [29] and IGrid [3], partitioning each dimension D of the search space in k D ranges.…”

Section: The Bitmatrix In MMDImentioning

confidence: 99%

An Evaluation Framework for Multidimensional Multimedia Descriptor Indexing

Gonalves

Ribeiro

Calistru

et al. 2007

2007 IEEE 23rd International Conference on Data Engineering Workshop

Self Cite

View full text Add to dashboard Cite

Automatic multimedia retrieval requires the use of complex features, which are typically captured by multidimensional descriptors. A basic operation in a multimedia retrieval system is similarity computation, making use of descriptor-dependant metrics. Many data structures have been proposed for managing the representation of multidimensional descriptors, each geared towards efficiency in some set of basic operations.The paper describes a framework for evaluating multidimensional descriptor indexing structures and reports a set of experiments with selected descriptors indexing methods. The extensibility of the framework is illustrated by incorporating a recently-proposed structure, the BitMatrix. Data sets and experiment conditions can be set up so as to provide results that can be used in the choice of appropriate indexing structures for a class of multimedia retrieval applications.

show abstract

“…In this section the focus is also maintained on high-dimensional indexing by presenting an indexing approach, BitMatrix, Calistru et al (2006) that satisfies most of the requirements previously identified, and has been successfully applied in video retrieval.…”

Section: Bitmatrix-based Multidimensional Indexingmentioning

confidence: 99%

“…The manual annotation alternative Shneiderman et al (2006), although essential in many cases, cannot keep the pace with the growth rate of video productions. On the other hand, if search relies on low-level similarity, in a query-by-example fashion, a short time to search can be achieved Calistru et al (2006); Tesic (2004). Two main directions can be followed: effectivity-oriented, where finding relevant objects is the priority, and efficiency-oriented, where the quality of results is traded for speed.…”

Section: Introductionmentioning

confidence: 99%